This “mathematics-friendly” volume introduces readers to basic concepts and applications of Statistical Process Control (SPC). Readers get a solid foundation in control charts—including setting scales, charting, interpreting, and analyzing process capability. Problem-solving techniques are emphasized, and all learning is linked to the implementation of SPC in the workplace. The volume offers an introduction to quality concepts and statistical process control, quality issues, variation and statistics, an introduction to tables, charts, and graphs, probability and the normal distribution, control charts, variables charts for limited data, attributes control charts, problem solving, gauge capability and acceptance sampling. For quality control trainers and quality management/improvement teams.

A highly successful title from one of the UK's leading exponents of TQM. The book features user-friendly presentation and reflects the latest thinking in the field. It will serve as a textbook for self or group instruction for both student and practicing engineers, scientists, technologists and managers and will prove invaluable to all. Statistical process control is a tool, which enables both manufacturers and suppliers to achieve control of product quality by means of the application of statistical methods in the controlling process. This book gives the foundations of good quality management and process control, including an explanation of what quality is, and control of conformance and consistency during production. The text offers clear guidance and help to those unfamiliar with either quality control or statistical applications and coves all the necessary theory and techniques in a practical and non-mathematical manner. This book will be essential reading for anyone wishing to understand or implement modern statistical process control techniques.

A statistical approach to the principles of quality control and management Incorporating modern ideas, methods, and philosophies of quality management, Fundamentals of Quality Control and Improvement, Fourth Edition presents a quantitative approach to management-oriented techniques and enforces the integration of statistical concepts into quality assurance methods. Utilizing a sound theoretical foundation and illustrating procedural techniques through real-world examples, the timely new edition bridges the gap between statistical quality control and quality management. Promoting a unique approach, the book focuses on the use of experimental design concepts as well as the Taguchi method for creating product/process designs that successfully incorporate customer needs, improve lead time, and reduce costs. The Fourth Edition of Fundamentals of Quality Control and Improvement also includes: New topical coverage on risk-adjustment, capability indices, model building using regression, and survival analysis Updated examples and exercises that enhance the readers’ understanding of the concepts Discussions on the integration of statistical concepts to decision making in the realm of quality assurance Additional concepts, tools, techniques, and issues in the field of health care and health care quality A unique display and analysis of customer satisfaction data through surveys with strategic implications on decision making, based on the degree of satisfaction and the degree of importance of survey items Fundamentals of Quality Control and Improvement, Fourth Edition is an ideal book for undergraduate and graduate-level courses in management, technology, and engineering. The book also serves as a valuable reference for practitioners and professionals interested in expanding their knowledge of statistical quality control, quality assurance, product/process design, total quality management, and/or Six Sigma training in quality improvement.

Written in clear language, this hands-on manual simplifies the essentials for monitoring, analyzing, and improving quality. The authors explain how to set up and use variable and attribute control charts, as well as analyze frequency histograms, and evaluate machine and process capability.

INCREASE your odds of learning STATISTICAL process control (SPC) Identify and reduce variation in business processes using SPC--the powerful analysis tool for process evaluation and improvement. Statistical Process Control Demystified shows you how to use SPC to enable data-driven decision making and gain a competitive advantage in the marketplace. Written in a step-by-step format, this practical guide explains how to analyze process data, collect data, and determine the suitability of a process in meeting requirements. Attribute and X-bar control charts are discussed, as are charts for individuals data. You'll also get details on process improvement and measurement systems analysis. Detailed examples, calculations, and statistical assumptions make it easy to understand the material, and end-of-chapter quizzes and a final exam help reinforce key concepts. It's a no-brainer! You'll learn about: Control chart interpretation Overcoming common errors in the use of SPC and general statistical analysis tools Sampling requirements Analysis using Excel Estimating process variation Designed experiments Measurement systems analysis, including R&R studies Continuous process improvement strategies Simple enough for a beginner, but challening enough for an advanced student, Statistical Process Control Demystified is your shortcut to this powerful analysis solution.

Do you feel you are drowning in a sea of data and wondering how you can learn from all of this information? While measuring quality efforts in healthcare is essential to the overall performance of any healthcare organization, it is also very complex, leaving many feeling overwhelmed and with a lot of unanswered questions: What are SPC methods and can they really help to improve healthcare? How can control charts be used to monitor key processes and outcomes? How can physicians use control charts to improve their clinical practice? In his latest book, Dr. Raymond Carey answers these questions and more as he helps to explain the need for, and the use of, SPC in healthcare. In Improving Healthcare with Control Charts: Basic and Advanced SPC Methods and Case Studies, Carey expands on his previous best-selling book, Measuring Quality Improvement in Healthcare, by providing more in-depth information on problems commonly experienced in constructing and analyzing control charts. He outlines specific SPC concepts, theories, and methods that will help improve measurement and therefore improve overall performance. Carey also presents many new case studies applying advanced methods and theory to real life healthcare situations.

This text provides the reader with a general and widely-applicable problem solving strategy for use in quality improvement. It covers a variety of statistical and "non-statistical" problem-solving tools, and discusses techniques that are useful when problems are solved by groups or teams of people. It also shows how the success of problem solving is influenced by the style of management and the type of management-employee interaction.

The trusted guide to the statistical methods for quality control. Quality control and improvement is more than an engineering concern. Quality has become a major business strategy for increasing productivity and gaining competitive advantage. Introduction to Statistical Quality Control, Sixth Edition gives you a sound understanding of the principles of statistical quality control (SQC) and how to apply them in a variety of situations for quality control and improvement. With this text, you′ll learn how to apply state–of–the–art techniques for statistical process monitoring and control, design experiments for process characterization and optimization, conduct process robustness studies, and implement quality management techniques. You′ll appreciate the significant updates in the Sixth Edition including: ∗ In–depth attention to DMAIC, the problem–solving strategy of Six Sigma. It will give you an excellent framework to use in conducting quality improvement projects. ∗ New examples that illustrate applications of statistical quality improvement techniques in non–manufacturing settings. Many examples and exercises are based on real data. ∗ New developments in the area of measurement systems analysis ∗ New features of Minitab V15 incorporated into the text ∗ Numerous new examples, exercises, problems, and techniques to enhance your absorption of the material

With its coverage of Food and Drug Administration regulations, international regulations, good manufacturing practices, and process analytical technology, this handbook offers complete coverage of the regulations and quality control issues that govern pharmaceutical manufacturing. In addition, the book discusses quality assurance and validation, drug stability, and contamination control, all key aspects of pharmaceutical manufacturing that are heavily influenced by regulatory guidelines. The team of expert authors offer you advice based on their own firsthand experience in all phases of pharmaceutical manufacturing.

This “mathematics-friendly” volume introduces readers to basic concepts and applications of Statistical Process Control (SPC). Readers get a solid foundation in control charts—including setting scales, charting, interpreting, and analyzing process capability. Problem-solving techniques are emphasized, and all learning is linked to the implementation of SPC in the workplace. The volume offers an introduction to quality concepts and statistical process control, quality issues, variation and statistics, an introduction to tables, charts, and graphs, probability and the normal distribution, control charts, variables charts for limited data, attributes control charts, problem solving, gauge capability and acceptance sampling. For quality control trainers and quality management/improvement teams.